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Target wave in the network coupled by thermistors

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  • Zhang, Xiufang
  • Yao, Zhao
  • Guo, Yeye
  • Wang, Chunni

Abstract

Pattern formation and synchronization stability in the network are dependent on the local kinetics, connection type, and property of coupling channel. The coupling channels is often controlled to reach synchronization and pattern selection. From dynamical viewpoint, all the bifurcation parameters and coupling channels can be adjusted to get desired patterns and behaviors. However, the physical parameters for most of the electronic components are fixed even some of them can be adjusted in slight range. Thermistor is a kind of nonlinear electronic components, and its resistance is dependent on the temperature completely. It can be used to detect the fluctuation of environment temperature by building nonlinear circuits composed of thermistors. The coupling channel can be adjusted by the temperature when the thermistors are used to couple two or more nonlinear circuits. In this paper, the thermistors are used to couple Chua circuits in a square array with regular connection between adjacent nodes in the network. Gradient distribution of temperature on the network can induce diversity in the coupling intensity in the network because the channel resistances of the coupling thermistors are influenced by the heterogeneous distribution of temperature. In fact, the nodes close to the heat source have higher temperature and they are coupled with stronger intensity because of lower resistances for the coupling thermistors. Perfect target waves can be induced and propagated in the network by taming the temperature for coupling channels. Furthermore, statistical synchronization factor is calculated to estimate the synchronization stability and wave propagation in the network. These results suggested that physical components with adjustable parameters can be used in practical control of nonlinear systems.

Suggested Citation

  • Zhang, Xiufang & Yao, Zhao & Guo, Yeye & Wang, Chunni, 2021. "Target wave in the network coupled by thermistors," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:chsofr:v:142:y:2021:i:c:s096007792030847x
    DOI: 10.1016/j.chaos.2020.110455
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    Cited by:

    1. Li, Fan & Liu, Shuai & Li, Xiaola, 2022. "Pattern selection in thermosensitive neuron network induced by noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).

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